package com.peng.leetcode.other;

import java.util.Comparator;
import java.util.HashMap;
import java.util.Map;
import java.util.PriorityQueue;

/**
 * MedianSlidingWindow
 * <p>
 * 480. 滑动窗口中位数
 *
 * @author: lupeng6
 * @create: 2021/2/3 15:19
 */
public class MedianSlidingWindow1 {

    class Solution {
        public double[] medianSlidingWindow(int[] nums, int k) {
            DualHeap dh = new DualHeap(k);
            for (int i = 0; i < k; ++i) {
                dh.insert(nums[i]);
            }
            double[] ans = new double[nums.length - k + 1];
            ans[0] = dh.getMedian();
            for (int i = k; i < nums.length; ++i) {
                dh.insert(nums[i]);
                dh.erase(nums[i - k]);
                ans[i - k + 1] = dh.getMedian();
            }
            return ans;
        }
    }

    class DualHeap {
        // 大根堆，维护较小的一半元素
        private PriorityQueue<Integer> small;
        // 小根堆，维护较大的一半元素
        private PriorityQueue<Integer> large;
        // 哈希表，记录「延迟删除」的元素，key 为元素，value 为需要删除的次数
        private Map<Integer, Integer> delayed;

        private int k;
        // small 和 large 当前包含的元素个数，需要扣除被「延迟删除」的元素
        private int smallSize, largeSize;

        public DualHeap(int k) {
            this.small = new PriorityQueue<Integer>(new Comparator<Integer>() {
                public int compare(Integer num1, Integer num2) {
                    return num2.compareTo(num1);
                }
            });
            this.large = new PriorityQueue<Integer>(new Comparator<Integer>() {
                public int compare(Integer num1, Integer num2) {
                    return num1.compareTo(num2);
                }
            });
            this.delayed = new HashMap<Integer, Integer>();
            this.k = k;
            this.smallSize = 0;
            this.largeSize = 0;
        }

        public double getMedian() {
            return (k & 1) == 1 ? small.peek() : ((double) small.peek() + large.peek()) / 2;
        }

        public void insert(int num) {
            if (small.isEmpty() || num <= small.peek()) {
                small.offer(num);
                ++smallSize;
            } else {
                large.offer(num);
                ++largeSize;
            }
            makeBalance();
        }

        public void erase(int num) {
            delayed.put(num, delayed.getOrDefault(num, 0) + 1);
            if (num <= small.peek()) {
                --smallSize;
                if (num == small.peek()) {
                    prune(small);
                }
            } else {
                --largeSize;
                if (num == large.peek()) {
                    prune(large);
                }
            }
            makeBalance();
        }

        // 不断地弹出 heap 的堆顶元素，并且更新哈希表
        private void prune(PriorityQueue<Integer> heap) {
            while (!heap.isEmpty()) {
                int num = heap.peek();
                if (delayed.containsKey(num)) {
                    delayed.put(num, delayed.get(num) - 1);
                    if (delayed.get(num) == 0) {
                        delayed.remove(num);
                    }
                    heap.poll();
                } else {
                    break;
                }
            }
        }

        // 调整 small 和 large 中的元素个数，使得二者的元素个数满足要求
        private void makeBalance() {
            if (smallSize > largeSize + 1) {
                // small 比 large 元素多 2 个
                large.offer(small.poll());
                --smallSize;
                ++largeSize;
                // small 堆顶元素被移除，需要进行 prune
                prune(small);
            } else if (smallSize < largeSize) {
                // large 比 small 元素多 1 个
                small.offer(large.poll());
                ++smallSize;
                --largeSize;
                // large 堆顶元素被移除，需要进行 prune
                prune(large);
            }
        }
    }


}
